Tomás Kren

According to our database, Tomás Kren authored at least 9 papers between 2014 and 2017.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2017

Automatic Creation of Machine Learning Workflows with Strongly Typed Genetic Programming.

Tomás Kren, Martin Pilát, Roman Neruda

Int. J. Artif. Intell. Tools, 2017

Multi-objective evolution of machine learning workflows.

Tomás Kren, Martin Pilát, Roman Neruda

Proceedings of the 2017 IEEE Symposium Series on Computational Intelligence, 2017

Combining top-down and bottom-up approaches for automated discovery of typed programs.

Tomás Kren, Josef Moudrík, Roman Neruda

Proceedings of the 2017 IEEE Symposium Series on Computational Intelligence, 2017

Algorithm Discovery with Monte-Carlo Search: Controlling the Size.

Josef Moudrík, Tomás Kren, Roman Neruda

Proceedings of the 29th IEEE International Conference on Tools with Artificial Intelligence, 2017

2016

Asynchronous Evolution of Data Mining Workflow Schemes by Strongly Typed Genetic Programming.

Martin Pilát, Tomás Kren, Roman Neruda

Proceedings of the 28th IEEE International Conference on Tools with Artificial Intelligence, 2016

2015

A Dynamic Programming Approach to Individual Initialization in Genetic Programming.

Tomás Kren, Roman Neruda

Proceedings of the 2015 IEEE International Conference on Systems, 2015

Generating Workflow Graphs Using Typed Genetic Programming.

Tomás Kren, Martin Pilát, Klára Pesková, Roman Neruda

Proceedings of the 2015 International Workshop on Meta-Learning and Algorithm Selection co-located with European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases 2015 (ECMLPKDD 2015), 2015

2014

Utilization of reductions and abstraction elimination in typed genetic programming.

Tomás Kren, Roman Neruda

Proceedings of the Genetic and Evolutionary Computation Conference, 2014

Generating lambda term individuals in typed genetic programming using forgetful A∗.

Tomás Kren, Roman Neruda

Proceedings of the IEEE Congress on Evolutionary Computation, 2014